Housing and healthcare devour 42% of the average American household's income, a stubborn tax on living that technology has failed to reduce—until now. EliseAI co-founders Mina and Tony join the podcast to break down how they’re using AI to attack the operational bloat in two of the economy’s most critical and inefficient sectors.
The Affordability Tax
AI as the Efficiency Engine
Unlocking Supply and Expanding to Healthcare
Key Takeaways:
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This episode reveals how AI is tackling the affordability crisis in housing and healthcare by automating the complex, inefficient operations that drive up costs for everyone.
The Mission: Using AI to Solve Real-World Economic Problems
Mina and Tony, co-founders of EliseAI, explain their motivation for targeting housing and healthcare. These two sectors represent a staggering 42% of a typical household's expenses and 40% of the entire US GDP. They argue that despite their massive economic impact, these industries have been largely untouched by top technology talent, leading to systemic inefficiencies that function as an "accepted tax" on society. Their goal is to apply AI to cut waste, reduce costs, and improve the quality of these essential services.
Alex, representing the investment perspective, frames the opportunity through a powerful economic chart showing that while technology has driven down costs for consumer goods like TVs and computers, housing and healthcare prices have only moved up. He notes that the current paradigm shift with AI presents a unique opportunity to finally address the immense operational and administrative burdens in these sectors.
Mina states, "It's pretty self-evident that technology makes the experience better for everyone and brings down costs and more people should be working on it."
The Housing Crisis: A Problem of Supply and Utilization
The conversation first dives into the housing affordability crisis, which Mina identifies as primarily a supply problem. The US is currently short about 5 million housing units and needs to build 1.8 to 2 million units annually just to keep the deficit from worsening. However, development is slowing, with projections showing a 50% drop in the pipeline for 2026 and beyond.
While building more is the long-term solution, Mina highlights that AI can improve the utilization of existing supply in the short term. She points out a critical inefficiency: almost half of all inquiries to rental buildings go unanswered. By automating responses and managing demand, AI can fill vacant apartments faster.
Unlocking Capital and Navigating Regulation
The discussion shifts to the bottlenecks preventing new housing supply: regulation and capital. While zoning laws are a significant hurdle, Mina argues that even with deregulation, more capital is needed for construction. Capital flows to assets with the highest returns, and housing currently offers lower returns compared to other classes.
EliseAI's strategy is to make housing a more attractive investment by creating "10x better housing operators." By using AI to streamline operations and increase profits, they aim to boost returns, attract more investment, and ultimately drive the construction of new supply.
Tony points to Minneapolis as a successful case study for regulatory reform. After the city ended single-family zoning in 2019, housing supply grew three times faster than the national average, and rents remained flat while the rest of the country saw a 31% increase. This provides a tangible example of how policy changes, known as YIMBYism (Yes In My Backyard), can directly impact housing availability and cost when paired with sufficient capital.
The Vision of Fully Autonomous Buildings
The ultimate goal for EliseAI is to enable fully autonomous buildings, where core operations run without human intervention. Mina explains that much of the day-to-day work in property management is administrative and can be automated. The remaining physical tasks, like maintenance, define the current limits of automation.
The impact of this automation is already significant. Alex highlights that Equity Residential, an EliseAI customer, has reached an efficiency of 200 units per employee—double the industry baseline. Another customer, Brookfield Properties, is using a centralized model where a single employee, supported by AI, can service up to 10,000 units.
Mina outlines the vision: "Our goal is to enable fully autonomous buildings. An entire portfolio has the ability to run core operations without requiring human intervention at all."
Tony adds that even the boundaries of physical work are shifting. Smart locks, for example, allow AI to handle key provisioning, and an increase in building sensors will enable AI to make more planning and maintenance decisions, further pushing the frontier of automation.
Redefining Human Roles in an AI-Powered Future
With AI automating administrative tasks, the conversation explores the future of human jobs in property management. Mina predicts that roles will not disappear but will evolve into "AI-enabled career paths." Freed from menial work, staff can focus on higher-value activities like building community relationships and creating a better resident experience.
New, specialized roles will emerge, such as renewal specialists for complex retention cases or resident experience specialists who resolve conflicts. In the long term, humans will transition to overseeing large workforces of AI agents and managing the automated systems that run the buildings.
The Long-Term Intersection of AI, Robotics, and Demographics
Looking ahead 10 years, the discussion considers the impact of robotics, longevity research, and AGI on housing. Mina connects AI-driven advances in longevity to population growth, noting that if people live longer and the cost of living decreases, birth rates may rise. This demographic shift would create even greater demand for housing.
This is where robotics becomes critical. Modular housing and robot-assisted construction could dramatically lower the cost and increase the speed of building new supply. Tony also emphasizes the importance of mobility, suggesting that AI can make it cheaper and easier for operators to handle shorter-term leases, giving people the flexibility to move for jobs or better quality of life without being locked into 12-month contracts.
From Housing to Healthcare: A Surprising Synergy
The conversation takes a fascinating turn as the team discusses EliseAI's expansion into healthcare. Alex admits his initial skepticism, but the healthcare business is now "humming." Tony explains that while the industries seem different, the administrative and operational problems are remarkably similar.
Both sectors suffer from bloated cost structures, staffing shortages, and complex digital-physical interactions governed by heavy regulation. Key workflows like patient or tenant intake involve collecting structured information and handling a high volume of repetitive inquiries.
Tackling Inefficiency in Healthcare
The team argues that while healthcare is an elastic good—meaning people will always want more and better care—the administrative side offers no such value. Costs on the admin side have skyrocketed without any improvement in the patient experience. AI is positioned to make a significant dent here.
The platform's future in healthcare extends beyond initial scheduling. The vision includes managing the entire administrative journey from the first interaction to the billing cycle. A major focus is on post-appointment patient engagement and adherence. AI can provide follow-up, answer questions, and educate patients and their families, improving treatment outcomes and reducing costs associated with non-adherence.
Conclusion: A Blueprint for AI in the Physical World
This episode provides a clear blueprint for how AI can drive efficiency and affordability in the economy's largest and most stagnant sectors. By automating complex operations, EliseAI is not just creating value for property owners and healthcare providers but is also directly addressing the cost-of-living crisis for consumers.
